inspire-group / modelpoisoning Goto Github PK

Hi,when I ran the code and then there's an error showed up
"ModuleNotFoundError: No module named 'tensorflow.compat'"

is there any suggestion to solve? Thanks.

The source code contains cifar_10_model, but I cannot find the definition, so I made a minor change on source code and did some experiments on cifar10 dataset.
However, the result shows that the malicious agent succeeded in 40 of 40 iterations with high confidence in both converge and dist strategy. Is that normal ?

I did not find the code for accuracy check as mentioned in this paper. Is the 'accuracy check' included in the source code? In other words, will the central server check the accuracy of model updates from different participants before aggregating them?

Further, would you please give the parameters (or a running command) to reproduce the results in the paper on attacking 'krum' and 'coomed' aggregation rule?

I find error about multiprocessing in my environment, so I change the Process to single thread, but I can't get the similar weights distribution results in your paper. My questions are:

1. What params should I add to get the results of "Alternating minimization with distances constraints" in your paper.
2. I find your params "--mal_strat=converge" in the code is useless, does it true? And how to adjust the params to make malicious agent attack at the convergence of model.
3. Does it have influence for weights distributions if I change it to single thread execution?

I ran the source code and still met many small errors. These errors are summarized below:

1. from mnist import * ==> from utils.mnist import *
   2 allow_pickle=True should be added to np.load

It seems that cifar_utils is missing, giving the following error when trying to train the model with the command written in readme

File "code/ModelPoisoning/agents.py", line 11, in
from cifar_utils import cifar_10_model
ImportError: No module named cifar_utils

Hi Arjun, I have reproduced the experiment of the alternating minimization attack following the command in README:

python dist_train_w_attack.py --dataset=fMNIST --k=10 --C=1.0 --E=5 --T=40 --train --model_num=0 --mal --mal_obj=single --mal_strat=converge_train_alternate_wt_o_dist_self --rho=1e-4 --gar=avg --ls=10 --mal_E=10

However, the result shows that "Malicious agent succeeded in 0 of 6 iterations". After checking the source code, I find that during the 6 iterations the global model correctly predicted the malicious data with the label "5". And the output file for predicting the malicious data is as following:

t,target,target_conf,actual,actual_conf
1,7,0.18352902,5,0.5428532
2,7,0.13259208,5,0.849949
3,7,0.04781367,5,0.9503012
4,7,0.09260346,5,0.9071523
5,7,0.48864973,5,0.51109886
6,7,0.48037982,5,0.5195737

The results are not consistent with the figures in the paper that show the global model misclassifies the malicious data in confidence nearly 1 after 3 iterations. So did I miss something? Why does it happend? Thanks.

Hi, I am trying to understand your code. But there is a problem that bothers me, why the default value of 'arg.mal' is True?
In my opinion, if this value is True, then the attack will be carried out. However, in your README, you wrote that 'To run federated training with 10 agents and standard averaging based aggregation, use
python dist_train_w_attack.py --dataset=fMNIST --k=10 --C=1.0 --E=5 --T=40 --train --model_num=0 --gar=avg'
So this code allows malicious clients to participate in training? Or just forgot to add --mal = False?
This question has been puzzling me for a long time, and I am looking forward to get your reply soon.
All the best!

I keep getting this error when I run the code, Can I get help, please? what I am doing wrong?

hello,Arjun.
When I ran the program according to README.md, there was an error that I cannot solve.
Traceback (most recent call last):
File "M:/Projects/Local model poison/ModelPoisoning/dist_train_w_attack.py", line 11, in
from utils.io_utils import data_setup, mal_data_setup
File "M:\Projects\Local model poison\ModelPoisoning\utils\io_utils.py", line 9, in
from mnist import data_mnist
ImportError: cannot import name 'data_mnist'
Is the package mnist or python-mnist necessacy? How can I solve this error?

hi,I tried to run the code and there's a problem that showed up

what should I do?

Hello,
Just out of curiosity, I wanted to know why were none of the federated learning libraries used in this code?
Thanks
Harshita